Test performance prediction method, apparatus, medium, and electronic equipment for test systems

Abstract

The present disclosure relates to a test performance prediction method of a test system. The invention relates to a device, a medium and an electronic device, belonging to the technical field of machine learning application. The method comprises the following steps of: climbing the data of a plurality of target indexes before a predetermined time point in turn, inputting the data into a data analysis system to carry out real-time test on the data analysis system, and sequentially outputting the test results; serially connecting the sequentially outputted test results to obtain a test result sequence; inputting the test result sequence into a pre-trained machine learning model, outputting a fluctuation curve with a time point as an abscissa after the predetermined time point by the machinelearning model, and predicting the test result data as a ordinate. According to the preset performance analysis method, the fluctuation curve is analyzed to obtain the test performance result of the test system. The present disclosure utilizes the test result sequence sample iterative training prediction machine learning model to accurately and efficiently implement the test performance predictionof the test system.

Description

technical field [0001] The present disclosure relates to the technical field of machine learning applications, and in particular, to a test performance prediction method, device, medium and electronic equipment of a test system. Background technique [0002] The data analysis system is a system that processes and organizes the data information of various indicators, calculates various analysis indicators, transforms them into information forms that are easy to be accepted by people, and stores the processed information. The test system for the data analysis system needs to test the data analysis system according to the requirements of each process of the data analysis system, and then obtain test results at different test time points. However, due to the initial fixed development environment of the test system, usually the test performance of the test system is limited within a certain period of time, and there will be performance bottlenecks, which cannot meet the subsequen...

AI Technical Summary

Problems solved by technology

However, due to the initial fixed development environment of the test system, the test performance of the test system is usually limited within a certain period of time, and there will be performance bottlenecks, which cannot meet the subsequent test requirements

At present, there is no method to predict the test performance of the test system at other time points after a certain test time point, resulting in the inability to adjust the test system in time, resulting in delays in various links such as software system development and use

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